Introduction¶

This dataset presents a comprehensive overview of rental property listings across multiple cities in the United Arab Emirates, including Abu Dhabi, Dubai, Sharjah, Ajman, Ras Al Khaimah, Umm Al Quwain, and Al Ain. Compiled from bayut.com, it is a valuable resource for Data Analysts, Data Scientists, and Researchers looking to explore real estate trends, rental pricing patterns, or urban development studies in the UAE.

Dataset Overview¶

Each entry in the dataset represents a rental property listing with details about the property's features, rental terms, and location specifics. This primary and unique dataset is designed for analysis and can be used to generate insights into the rental market dynamics of the UAE.

Usage¶

This dataset is open for public use and is particularly suited for:

Analyzing trends in the rental market. Studying the geographical distribution of rental properties. Comparing rental prices across different cities and property types. Developing machine learning models to predict rental prices or classify property types.

In [1]:
import pandas as pd

# Load your dataset
df = pd.read_csv('dubai_properties.csv')
df.columns
df
Out[1]:
Address Rent Beds Baths Type Area_in_sqft Rent_per_sqft Rent_category Frequency Furnishing Purpose Posted_date Age_of_listing_in_days Location City Latitude Longitude
0 The Gate Tower 2, The Gate Tower, Shams Gate D... 124000 3 4 Apartment 1785 69.467787 Medium Yearly Unfurnished For Rent 2024-03-07 45 Al Reem Island Abu Dhabi 24.493598 54.407841
1 Water's Edge, Yas Island, Abu Dhabi 140000 3 4 Apartment 1422 98.452883 Medium Yearly Unfurnished For Rent 2024-03-08 44 Yas Island Abu Dhabi 24.494022 54.607372
2 Al Raha Lofts, Al Raha Beach, Abu Dhabi 99000 2 3 Apartment 1314 75.342466 Medium Yearly Furnished For Rent 2024-03-21 31 Al Raha Beach Abu Dhabi 24.485931 54.600939
3 Marina Heights, Marina Square, Al Reem Island,... 220000 3 4 Penthouse 3843 57.246942 High Yearly Unfurnished For Rent 2024-02-24 57 Al Reem Island Abu Dhabi 24.493598 54.407841
4 West Yas, Yas Island, Abu Dhabi 350000 5 7 Villa 6860 51.020408 High Yearly Unfurnished For Rent 2024-02-16 65 Yas Island Abu Dhabi 24.494022 54.607372
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
73737 Al Huboob 1, Al Salamah, Umm Al Quwain 14000 0 1 Apartment 419 33.412888 Low Yearly Unfurnished For Rent 2023-12-14 129 Al Salamah Umm Al Quwain 25.493412 55.575994
73738 Umm Al Quwain Marina, Umm Al Quwain 14000 0 1 Apartment 500 28.000000 Low Yearly Unfurnished For Rent 2023-12-14 129 Umm Al Quwain Marina Umm Al Quwain 25.527959 55.606527
73739 King Faisal Street, Umm Al Quwain 50000 3 4 Apartment 2000 25.000000 Low Yearly Unfurnished For Rent 2024-01-02 110 King Faisal Street Umm Al Quwain NaN NaN
73740 Al Maqtaa, Umm Al Quwain 37000 1 2 Apartment 989 37.411527 Low Yearly Unfurnished For Rent 2023-10-23 181 Al Maqtaa Umm Al Quwain NaN NaN
73741 Al Rass, Umm Al Quwain 11000 0 1 Apartment 300 36.666667 Low Yearly Unfurnished For Rent 2024-02-12 69 Al Rass Umm Al Quwain NaN NaN

73742 rows × 17 columns

In [2]:
# Explore the data
print(df.head())  # Display the first few rows

                                             Address    Rent  Beds  Baths  \
0  The Gate Tower 2, The Gate Tower, Shams Gate D...  124000     3      4   
1                Water's Edge, Yas Island, Abu Dhabi  140000     3      4   
2            Al Raha Lofts, Al Raha Beach, Abu Dhabi   99000     2      3   
3  Marina Heights, Marina Square, Al Reem Island,...  220000     3      4   
4                    West Yas, Yas Island, Abu Dhabi  350000     5      7   

        Type  Area_in_sqft  Rent_per_sqft Rent_category Frequency  \
0  Apartment          1785      69.467787        Medium    Yearly   
1  Apartment          1422      98.452883        Medium    Yearly   
2  Apartment          1314      75.342466        Medium    Yearly   
3  Penthouse          3843      57.246942          High    Yearly   
4      Villa          6860      51.020408          High    Yearly   

    Furnishing   Purpose Posted_date  Age_of_listing_in_days        Location  \
0  Unfurnished  For Rent  2024-03-07                      45  Al Reem Island   
1  Unfurnished  For Rent  2024-03-08                      44      Yas Island   
2    Furnished  For Rent  2024-03-21                      31   Al Raha Beach   
3  Unfurnished  For Rent  2024-02-24                      57  Al Reem Island   
4  Unfurnished  For Rent  2024-02-16                      65      Yas Island   

        City   Latitude  Longitude  
0  Abu Dhabi  24.493598  54.407841  
1  Abu Dhabi  24.494022  54.607372  
2  Abu Dhabi  24.485931  54.600939  
3  Abu Dhabi  24.493598  54.407841  
4  Abu Dhabi  24.494022  54.607372
In [3]:
print(df.describe())  # Summary statistics

               Rent          Beds         Baths   Area_in_sqft  Rent_per_sqft  \
count  7.374200e+04  73742.000000  73742.000000   73742.000000   73742.000000   
mean   1.479250e+05      2.162811      2.650213    2054.053552      88.057754   
std    3.069658e+05      1.578155      1.632997    3003.919252      66.534400   
min    0.000000e+00      0.000000      1.000000      74.000000       0.000000   
25%    5.499900e+04      1.000000      2.000000     850.000000      39.977778   
50%    9.800000e+04      2.000000      2.000000    1334.000000      71.428571   
75%    1.700000e+05      3.000000      3.000000    2130.000000     118.483412   
max    5.500000e+07     12.000000     11.000000  210254.000000    2182.044888   

       Age_of_listing_in_days      Latitude     Longitude  
count            73742.000000  73023.000000  73023.000000  
mean                74.261547     24.918929     55.053133  
std                 72.346767      0.569356      0.653722  
min                 11.000000     15.175847     43.351928  
25%                 30.000000     24.493598     54.607372  
50%                 52.000000     25.078641     55.238209  
75%                 95.000000     25.197978     55.367138  
max               2276.000000     25.920310     56.361294
In [4]:
print(df.isnull().sum())  # Check for missing values

Address                     0
Rent                        0
Beds                        0
Baths                       0
Type                        0
Area_in_sqft                0
Rent_per_sqft               0
Rent_category               0
Frequency                   0
Furnishing                  0
Purpose                     0
Posted_date                 0
Age_of_listing_in_days      0
Location                    0
City                        0
Latitude                  719
Longitude                 719
dtype: int64

More Information¶

  1. Dataset Structure:

The dataset consists of 73,742 rows and 17 columns.

  1. Main Features of Interest:

The primary features of interest in this dataset are:

Address: Full address of the property.

Rent: The annual rent price in AED.

Beds: Number of bedrooms in the property.

Baths: Number of bathrooms in the property.

Type: Type of property (e.g., Apartment, Villa, Penthouse).

Area_in_sqft: Total area of the property in square feet.

Rent_per_sqft: Rent price per square foot, calculated as Rent divided by Area_in_sqft.

Rent_category: Categorization of the rent price (Low, Medium, High) based on thresholds.

Frequency: Rental payment frequency, which is consistently 'Yearly'.

Furnishing: Furnishing status of the property (Furnished, Unfurnished).

Purpose: The purpose of the listing, typically 'For Rent'.

Posted_date: The date the property was listed for rent.

Age_of_listing_in_days: The number of days the listing has been active since it was posted.

Location: A more specific location within the city where the property is located.

City: City in which the property is situated.

Latitude, Longitude: Geographic coordinates of the property.

  1. Supporting Features:

The following features are likely to be helpful in further investigating the features of interest:

City: City in which the property is situated.

Number of Properties: This can provide insights into market trends and availability.

Latitude, Longitude: Geographic coordinates for spatial analysis.

Address: Specific location details.

Furnishing: Furnishing status of the property.

Type: Type of property (e.g., Apartment, Villa, Penthouse).

Questions¶

We will use this visualization to answer the following questions:

What is the number of rental properties in each city?

Where are the rental properties located within the UAE?

Which city has the highest average rent?

How does the type of property affect the rent price?

In [5]:
import plotly.express as px
# What is the number of rental properties in each city?

city_distribution = df['City'].value_counts().reset_index()
city_distribution.columns = ['City', 'Number of Properties']

fig = px.bar(city_distribution, x='City', y='Number of Properties', 
             title='Rental Property Distribution by City', 
             labels={'Number of Properties': 'Number of Properties'})
fig.update_layout(xaxis_title='City', yaxis_title='Number of Properties')
fig.show()
In [6]:
#Where are the rental properties located within the UAE?

fig = px.scatter_mapbox(df, lat="Latitude", lon="Longitude", hover_name="Address", hover_data=["Rent", "Beds", "Baths"],
                        color_discrete_sequence=["fuchsia"], zoom=5, height=600)

     
fig.update_layout(mapbox_style="open-street-map")
fig.update_layout(title='Rental Properties Locations in UAE')

 
fig.show()
In [7]:
import matplotlib.pyplot as plt
import seaborn as sns

# Which city has the highest average rent?

plt.figure(figsize=(10, 8))
sns.scatterplot(x='City', y='Rent', data=df, hue='Furnishing')
plt.title('Rent vs. City by Furnishing')
plt.xlabel('City')
plt.ylabel('Rent')
plt.show()
In [8]:
# How does the type of property affect the rent price?

plt.figure(figsize=(16, 12))
sns.boxplot(x='Type', y='Rent', data=df)
plt.title('Rent Distribution by Type')
plt.xlabel('Type')
plt.ylabel('Rent')
plt.show()

Conclusion¶

From these results, we can conclude that:

Dubai has the highest number of rental properties and the highest average rent, while Fujairah has the lowest number of rental properties and the lowest average rent.

Within Dubai, the map shows that the highest rent is 1,100,000 AED in Umm Al Quwain Marina, Umm Al Quwain, and the lowest rent is 14,000 AED in Jebel Ali. Therefore, Umm Al Quwain Marina, Umm Al Quwain, appears to be the most profitable area for renters.

It is evident that villas are the most common type of property available for rent.